Practice Dynamic Programming Approach - 3.4 | 3. Common Subwords and Subsequences | Design & Analysis of Algorithms - Vol 3
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Dynamic Programming Approach

3.4 - Dynamic Programming Approach

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is a subword?

💡 Hint: Think about how you can take parts of a word

Question 2 Easy

What is the time complexity of the brute-force algorithm for finding longest common subwords?

💡 Hint: Consider how many comparisons you are making.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the focus of the longest common subword problem?

Finding the subword itself
Determining the length of the longest subword
Identifying mismatched characters

💡 Hint: Remember that we start by calculating length before deriving the subword.

Question 2

True or False: The brute-force algorithm is the most efficient method for finding the longest common subword.

True
False

💡 Hint: Consider the time complexity of brute-force versus dynamic programming.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given the strings 'abcdef' and 'zabcyfd', what is the length of the longest common subword?

💡 Hint: Consider breaking down each string and checking for the longest matching segment.

Challenge 2 Hard

Implement a table to compute the longest common subword length between 'hello' and 'world'. Analyze and explain your results.

💡 Hint: Map the characters in a grid to visualize matches.

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